Impact of climate-smart agricultural technology on multidimensional poverty in rural Ethiopia

A large body of empirical literature showed that the adoption of agricultural technologies reduces poverty. However, dominants of those studies so far used one-dimensional income or expenditure-based measures of poverty which may not reflect other types of deprivations. Therefore, the major objective of this study is to examine the impact of adopting climate-smart agricultural technology, which refers to a joint application of row planting methods and the use of chemical fertilizers, on the multidimensional poverty status of rural households in Ethiopia. To estimate the impact of the stated technologies, this study employs propensity score matching and endogenous switching regression methods. To measure the multidimensional poverty index, the study also uses the Alkire and Foster counting approach. Using the Ethiopian Socioeconomic Survey(ESS), collected in 2015-Wave 3, the results of the study show that the adoption of these technologies reduces deprivation score and one of its component, the standard of living part. Regionally, a high reduction in deprivation is observed in Amhara and Oromiya regions. The results also show that the impact is significantly higher in severely deprived households. It is also observed that the reduction in multidimensional poverty due to the technology is through an increase in income/consumption via improvement in production gain. The impact channels more through the non-food expenditure pathway. Finally, this study also sheds light on the effects that technology adoption has on multidimensional poverty reduction.

Fiscal Livelihood Spending’s Effects on Multidimensional Poverty Reduction in China

This paper investigates how fiscal spending on livelihood improves multidimensional household poverty in China.Based on the panel data of the“China Health and Nutrition Survey”(CHNS)for 2004-2015,we measured the chronic multidimensional poverty index for Chinese households.We have created a multitiered model for empirical analysis.Our findings suggest that multidimensional poverty in China is predominantly capacity poverty.Fiscal spending on livelihoods significantly reduces multidimensional poverty for Chinese households,especially rural households.Investments on livelihoods are more poverty-reducing than transfer spending on livelihoods.As an innovation,this paper offers a dynamic analysis of the effects of livelihood spending on multidimensional household poverty controlling for heterogeneity between individual households and across regions.Our conclusion suggests that the government should improve policy arrangements to increase social opportunities and support sustainable development capacities for the poor,while enhancing protective social security systems.

Measuring Multidimensional Poverty Reduction for the Chinese Elderly——Based on 2010 and 2016 Data from the China Family Panel Studies(CFPS)

Based on data gathered from the China Family Panel Studies(CFPS)in 2010 and 2016,this paper examines income poverty and multidimensional poverty among the Chinese elderly.Compared with the non-elderly population,poverty incidence was relatively lower among China’s elderly population in 2010,but the elderly poor were significantly more poor.By 2016,the level of poverty became more or less the same between elderly and non-elderly people.Compared with 2010,the poverty incidence on various deprived dimensions and the average share of deprivation for the elderly fell sharply in 2016 by an average of 30 and 10 percentage points,respectively.Reduction in poverty incidence was 10 percentage points higher for the rural elderly than for the urban elderly.After estimating the multidimensional poverty index for the elderly by the“two no worries and three guarantees”criteria,we found that the intensity of multidimensional poverty was only about half that of the income poverty.The“two worries,”i.e.the lack of food and clothing,contributed more to multidimensional poverty than did what the“three guarantees”target i.e.education,healthcare and housing,especially on income and residential energy dimensions.Elderly healthcare contributed more than 20%to the“three guarantees.”

Using Multiple Correspondence Analysis to Measure Multidimensional Poverty in Congo

The following analysis is based on a multidimensional understanding of poverty using a nonmonetary basic needs approach. It is ground on data from the first survey on household living conditions for poverty assessment, conducted by the National Institute of Statistics of Congo in 2005. Multiple Correspondence Analysis is applied to construct a composite indicator by aggregating several attributes likely to reflect the poverty of individuals or households. The application shows that Congolese households are not affected by the same type of poverty. Three types of non-monetary poverty are identified: infrastructure poverty, vulnerability of human existence and poverty of comfort. These households were then classified according to the composite indicator of Poverty. The results show that the incidence of poverty corresponds to the weight of poor class of about 70.67%.

Village-level multidimensional poverty measurement in China: Where and how

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error(LSE) model and spatial econometric analysis model to identify the villages' poverty types and poverty difference. The case study shows that:(1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang.(2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions.(3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type.(4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of pov-erty alleviation at all levels to mobilize all kinds of anti-poverty resources.

Analyzing multidimensional measures of poverty and their influences in China's Qinba Mountains

We use the Alkire–Foster poverty measure and decomposition method to study multidimensional poverty in the Qinling–Daba contiguous poor area of China's Henan Province.We examine absolute,relative,and multidimensional poverty focusing on heads of household and family characteristics as constituents of escaping each.We find that the multidimensional poverty index declines to a low level as values of k increase.Combining first-order random dominance with second-order stochastic dominance quickly determines rankings in the multidimensional poverty index.Increasing non-agricultural income emerges as the most important influence on escaping rural poverty,whereas households with elderly and children are at greatest risk for falling into poverty.

Eliminating poverty through development:The dynamic evolution of multidimensional poverty in rural China

This paper measures intertemporal multidimensional poverty in rural China from 1988 to 2018 based on the China Household Income Project(CHIP)data and for that time period has the following findings.First,multidimensional poverty in rural China declines steadily when measured through the income poverty approach.Second,multidimensional poverty in rural areas presents demographic and regional heterogeneity,among which elderly poverty,child poverty,and poverty in the western Chinese region are the most prominent ones.Third,income poverty and multidimensional poverty have a low overlap ratio and show intertemporal synchronisation over time.Although increases in income can alleviate multidimensional poverty,this effect is very limited.This paper suggests that a suitable multidimensional poverty identification framework should be developed in the era of poverty alleviation after 2020 and that in the new poverty alleviation governance system of China,targeted development strategies should be formulated with an increased focus on the poverty of special groups such as children and the elderly.

Identification and alleviation pathways of multidimensional poverty and relative poverty in counties of China

To realize efficient and sustainable poverty alleviation,this study firstly investigated the identification of multidimensional poverty and relative poverty,and then explored relevant poverty alleviation pathways.Poverty levels in 31 provinces including the autonomous regions and municipalities of China were identified at the county level using the average nighttime light index(ANLI),county multidimensional development index(CMDI),and a method combining multidimensional poverty index and relative poverty standards.Poverty alleviation pathways for poverty-stricken counties were explored from the aspects of industry,education,tourism and agriculture.The results revealed that nearly 60% of counties in China were primarily under relative poverty,most of which were corresponded to light relative poverty.In terms of ANLI and CMDI,63% and 79% of the national poverty-stricken counties,as of 2018,could be identified,suggesting that CMDI had a higher performance for identifying poverty at the county level.In terms of poverty alleviation pathways,414,172,442,and 298 poverty-stricken counties were receptive to industry poverty alleviation,education poverty alleviation,tourism poverty alleviation,and agriculture poverty alleviation,and 61%of counties had more poverty-causing factors,implying that multidimensional poverty alleviation is suitable in most of the counties.

Differences and dynamics of multidimensional poverty in rural China from multiple perspectives analysis

Absolute poverty was completely eliminated in China in 2020.However,poverty measured by income does not fully reflect the actual situation.This paper analyses multidimensional poverty and its dynamics in rural China from perspectives of region,terrain,and geographical location during 2010–2018.We use the Chinese Family Panel Survey data,adopt the Alkire-Foster method and improve the multidimensional poverty index(MPI),calculating and comparing multidimensional poverty and its dynamics among 3009 rural households.In addition,the contribution of the indicator to multidimensional poverty is decomposed.The results indicate that multidimensional poverty has obvious regional differences,topographical differences,and geographical differences.Moreover,the targeted poverty alleviation policy has a significant impact on multidimensional poverty eradication,and the rate of decline of the MPI during 2016–2018 is significantly greater than that of 2010–2014.Education contributes more than 50%to the MPI.In general,the proportion of households with persistent multidimensional poverty is higher than temporary multidimensional poverty,and temporary multidimensional poverty is higher than no multidimensional poverty.These results obtained from a large scale,long time and multiple perspectives could offer new insights for the government to further consolidate the results of poverty alleviation while offering China’s experience to other developing countries.

Understanding the multidimensional poverty in South Asia

Special attention needs to be paid to achieve the world’s poverty reduction goal by 2030 in less than ten-year time.The paper aims to investigate the multidimensional poverty in South Asia in the period 2003-2019.It constructs the Multidimensional Poverty Index(MPI)by selecting ten indicators in the fields of health,education and living standards.The research results show that the MPI of South Asia decreases in the research period.Poor people in South Asian countries are still facing several forms of deprivation while cooking fuel,sanitation,housing,nutrition and years of schooling are the main restrictive factors to poverty reduction in this region.Pakistan,India and Bangladesh face the worst poverty situation in terms of health,education and living standards.Targeted poverty alleviation and resilient poverty reduction are proposed in the paper to improve the poverty reduction efficiency and individual/regional capacity against risks to avoid returning to poverty.

Multidimensional poverty and types of impoverished counties in Gansu province of China

Gansu province,considered as one of the poorest provinces in China,faces great challenges in fighting against poverty.This study highlights the importance of studying multidimensional poverty in Gansu province.The Multidimensional Poverty Indices of 75 poverty-stricken counties in Gansu province are measured quantitatively.The main driving factors of poverty are identified through the construction and application of a multidimensional poverty measurement system,classifying the impoverished counties into several categories.This study provides a scientific basis for formulating effective policies to achieve sustainable poverty reduction and highquality development in the region after 2020.The results show that:(1)more than half of the poverty-stricken counties in Gansu province have a degree of multidimensional poverty that is below the median poverty level,with regional variations;(2)the main factors driving poverty in these counties include shortages in water and land resources,educational disruptions,undesirable medical conditions,and the underutilisation of labour,which show spatial variations;and(3)these poverty-stricken counties are categorised into four types:counties with fragile ecological environments and insufficient natural resources,counties with undesirable socio-economic conditions,counties with unfavourable conditions in development,and counties with relatively balanced development conditions.Finally,this paper proposes policy recommendations to achieve stable poverty alleviation based on different types of impoverished counties.

Multidimensional Relative Poverty of Farmers in Tibetan Areas - Based on a Data Analysis on Micro Surveys

In 2020,the issue of absolute poverty has been solved,and China is building a well-off society in an all-round way.The issue of relative poverty is an important content of poverty reduction.Based on a survey data from Danba County in October 2020,this paper uses the AF method to calculate the incidence of multidimensional poverty and the multidimensional poverty index.The results showed that 44.65%of the farmers have multidimensional deprivation of any three indicators of relative poverty,and 2.79%of the farmers have serious multidimensional deprivation;the incidence of one-dimensional poverty in terms of“educational level index of head of household,”“per capita non-transfer income of households in 2019,”and“per capita household income in 2019”is the highest;at the same time,the contribution rate of the three indicators to the multidimensional poverty index is also higher than other indicators.Therefore,several suggestions have been put forward to alleviate the multidimensional relative poverty in the region from the aspects of industry development and education.

CCT and Rural Long-Term Poverty Reduction:International Experiences and China’s Practice

China’s anti-poverty strategy in the post-2020 era will focus on reducing chronic poverty and alleviating relative poverty.As a common international approach for long-term multidimensional poverty reduction,conditional cash transfer(CCT)payments reduce current poverty,prevent future poverty,and improve income distribution by providing poor households with cash allowances and promoting children’s human capital accumulation.For such reasons,CCT serves as an anti-poverty policy instrument worth referencing for China.This paper systematically reviewed the theoretical basis and development journey of CCT,the short-term and long-term implementation effects,as well as the decision-making basis,design and potential limitations.In this paper,we have further analyzed the poverty-reducing effects and problems of China’s rural public transfer payment policies in the current stage and discussed the achievements and inadequacies of China’s ongoing CCT pilot programs.Results indicate that the further development of CCT in China calls for a combination top-down and bottom-up policy-making approaches in project design and implementation,as well as an evolving poverty governance system complementary with other relevant policies.

Targeted Poverty Alleviation Lies in Precisely Identifying the Poverty–Stricken Population: An Analysis of the Targeting Effect of the Rural Subsistence Allowance Policy

Poverty–stricken populations must be identified precisely in the fight against poverty to implement the strategy of building a moderately prosperous society in all respects by 2020. The analysis based on the household survey in 2013 shows that the targeting accuracy is not high based on the standard of income and the accuracy is higher based on the standard of multidimensional poverty index. But the latter still has a low coverage rate. To gradually achieve integration of the rural poverty line and the rural subsistence allowance line, standards applied to identifying households entitled to subsistence allowances should be changed from the standard of income to multidimensional poverty indexes. A unified standard of subsistence allowances and a unified method for identifying related households should be developed. At the same time, coverage and funding of subsistence allowances should be extended and increased to better meet people's basic needs.

Multidimensional measurement of poverty and its spatio-temporal dynamics in China from the perspective of development geography

Exploring the spatio-temporal dynamics of poverty is important for research on sustainable poverty reduction in China. Based on the perspective of development geography, this paper proposes a panel vector autoregressive(PVAR) model that combines the human development approach with the global indicator framework for Sustainable Development Goals(SDGs) to identify the poverty-causing and the poverty-reducing factors in China. The aim is to measure the multidimensional poverty index(MPI) of China’s provinces from 2007 to 2017, and use the exploratory spatio-temporal data analysis(ESTDA) method to reveal the characteristics of the spatio-temporal dynamics of multidimensional poverty. The results show the following:(1) The poverty-causing factors in China include the high social gross dependency ratio and crop-to-disaster ratio, and the poverty-reducing factors include the high per capita GDP, per capita social security expenditure, per capita public health expenditure, number of hospitals per 10,000 people, rate of participation in the new rural cooperative medical scheme, vegetation coverage, per capita education expenditure, number of universities, per capita research and development(R&D) expenditure, and funding per capita for cultural undertakings.(2) From 2007 to 2017, provincial income poverty(IP), health poverty(HP), cultural poverty(CP), and multidimensional poverty have been significantly reduced in China, and the overall national poverty has dropped by 5.67% annually. there is a differentiation in poverty along different dimensions in certain provinces.(3) During the study period, the local spatial pattern of multidimensional poverty between provinces showed strong spatial dynamics, and a trend of increase from the eastern to the central and western regions was noted. The MPI among provinces exhibited a strong spatial dependence over time to form a pattern of decrease from northwestern and northeastern China to the surrounding areas.(4) The spatio-temporal networks of multidimensional poverty in adjacent provinces were mainly negatively correlated, with only Shaanxi and Henan, Shaanxi and Ningxia, Qinghai and Gansu, Hubei and Anhui, Sichuan and Guizhou, and Hainan and Guangdong forming spatially strong cooperative poverty reduction relationships. These results have important reference value for the implementation of China’s poverty alleviation strategy.

Geographical patterns and anti-poverty targeting post-2020 in China

Poverty has been a focus of Chinese government for a long time. It is therefore of great significance to investigate both the mechanisms and spatial patterns of regional impoverishment in order to adequately target Chinese anti-poverty goals. Based on the human-environment relationship and multidimensional poverty theory, this study initially develops a three-dimensional model encompassing human, society, and environmental factors to investigate the mechanisms of rural impoverishment as well as to construct an indicator system to evaluate the comprehensive poverty level(CPL) in rural areas. A back propagation neural network model was then applied to measure CPL, and standard deviation classification was used to identify counties that still require national policy-support(CRNPSs) subsequent to 2020. The results of this study suggest that CPL values conform to a decreasing trend from the southeast coast towards the inland northwest of China. Data also show that 716 CRNPSs will be present after 2020, mainly distributed in high-arid areas of the Tibetan Plateau, the transitional zones of the three-gradient terrain, as well as karst areas of southwest China. Furthermore, CRNPSs can be divided into four types, that is, key aiding counties restricted by multidimensional factors, aiding counties restricted by human development ability, aiding counties restricted by both natural resource endowment and socioeconomic development level, and aiding counties restricted by both human development ability and socioeconomic development level. We therefore propose that China should develop and adopt scientific and targeted strategies to relieve the relative poverty that still exist subsequent to 2020.

Exploring China's Potential Child Poverty

This paper estimates child poverty in China using 20IS data from the China Household Income Project.Applying the Alkire-Foster drawer approach,we constructed a multidimensional poverty indicator system that accounted for multiple factors contributing to a child's development and well-being,based on which we estimated multidimensional poverty experienced by children.Children s poverty varied by age,gender,rural/urban settings,and geographic region.By extending the Alkire-Foster drawer approach,two important features of child poverty in China were found,which had normally been neglected by per capita poverty measures:poor children in nonpoor families and unequal allocations to different children within the same families.The results showed that more than 40 percent of multidimensionally poor children lived in nonpoor families.Unequal resource allocation within families was observed in half of the families.These two features of child poverty require more policy attention and the Chinese government should prioritize addressing multidimensional child poverty.